Grad Sem

What it does

When your agent uses it

• The user needs to validate latent constructs
• Moderation paths
• Assess model fit with CFI/TLI/RMSEA/SRMR
• They ask do these variables form a causal chain

Example prompts

• “do these variables form a causal chain”
• “how do I test my theoretical model”
• “is my measurement model valid”
• “/grad-sem”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

1. 1Specify the Measurement Model
2. 2Assess Measurement Model Fit
3. 3Specify and Estimate the Structural Model
4. 4Report and Interpret

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grad Sem loads about 1.2k tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 400 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~111

When it runs · the whole SKILL.md, loaded when a task matches

~1.2k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 400 words, ~1,153 tokens.

name

grad-sem

description

Apply Structural Equation Modeling (SEM) to test hypothesized causal structures by combining measurement models (CFA) and structural models (path analysis). Use this skill when the user needs to validate latent constructs, test mediation or moderation paths, assess model fit with CFI/TLI/RMSEA/SRMR, or when they ask 'do these variables form a causal chain', 'how do I test my theoretical model', or 'is my measurement model valid'.

metadata.category

WP-31 量化方法

metadata.tags

SEM, structural-equation-modeling, CFA, path-analysis, model-fit, latent-variable

IRON LAW: SEM does NOT prove causation — it tests whether data is CONSISTENT
with a hypothesized causal structure. Good fit does NOT mean the model is
correct; it means the model cannot be rejected.

## SEM Analysis: [Study Title]

### Measurement Model (CFA)
| Construct | Indicator | Std. Loading | AVE | CR |
|-----------|-----------|-------------|-----|-----|
| [name] | [item] | x.xx | x.xx | x.xx |

### Model Fit
| Index | Value | Threshold | Assessment |
|-------|-------|-----------|------------|
| CFI | x.xx | ≥ 0.90 | [pass/fail] |
| TLI | x.xx | ≥ 0.90 | [pass/fail] |
| RMSEA | x.xx | ≤ 0.08 | [pass/fail] |
| SRMR | x.xx | ≤ 0.08 | [pass/fail] |

### Structural Paths
| Path | Std. β | S.E. | p-value | Supported? |
|------|--------|------|---------|------------|
| X → M | x.xx | x.xx | x.xx | [Yes/No] |

### Key Findings
- [Interpretation of results]

### Limitations
- [Note any assumption violations]

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in grad-sem of asgard-ai-platform/skills.

• SKILL.md
• examples/sample_scenario.md
• references/estimation.md

Open the folder on GitHubat commit 4e7f4f8